CN113776521B - Light intensity self-adaption method for Mars APS sun sensor - Google Patents

Light intensity self-adaption method for Mars APS sun sensor Download PDF

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CN113776521B
CN113776521B CN202111094499.3A CN202111094499A CN113776521B CN 113776521 B CN113776521 B CN 113776521B CN 202111094499 A CN202111094499 A CN 202111094499A CN 113776521 B CN113776521 B CN 113776521B
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CN113776521A (en
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张建福
张琳
常晔
刘建军
陈建新
李志平
李连升
尹路
高长山
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Beijing Institute of Control Engineering
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Abstract

The invention relates to a light intensity self-adaptive method of an APS sun sensor of a Mars vehicle, which creatively provides an automatic adjustment control method of integration time based on a high gray level threshold and a low gray level threshold by combining with the characteristic of sun spots of the APS sun sensor. In the capturing mode, the integral time is coarse-tuned, only the sun is captured, but the attitude is not output, the integral time is fine-tuned after tracking is carried out, and the attitude calculation is carried out after the proper integral time is obtained. The invention has larger criterion of integration time, fine adjustment of integration time in tracking mode, adjustment according to the step distance of 1, and fine judgment of integration time, and the highest gray distribution of solar bright spots is near 80% of saturation point, thus being suitable for Mars surface application.

Description

Light intensity self-adaption method for Mars APS sun sensor
Technical Field
The invention belongs to the field of optical attitude sensors, and relates to a light intensity self-adaption method of an APS sun sensor of a Mars vehicle.
Background
The sun sensor is an optical attitude sensor for measuring the included angle between the attitude of a spacecraft and the vector of solar rays by taking the sun as a reference azimuth. The sun vector direction is measured by a sun sensor on the Mars, yaw direction is provided for the Mars to travel on the surface of the Mars, the Mars is ensured to advance according to a preset direction, and meanwhile correction of long-time drift of the gyroscope is completed.
On the earth orbit, the solar light intensity is 1390W/m 2 The solar light intensity on the moon was 1414W/m 2 The distance between the earth and the sun is far more than that between the Mars and the sun, and the maximum value of the solar irradiation intensity of the Mars atmospheric layer is 717W/m 2 Minimum value is 493W/m 2 Average value of about 589W/m 2 About 42% of the solar radiation intensity near the earth; the intensity of solar radiation near the Mars varies by about + -19% in one Mars year, while the intensity of solar radiation near the earth varies by only + -3.5% in one earth year. The optical depth τ of visible light on Mars land is typically 0.5, according to the formula i=i 0 * exp (- τ), intensity of light I 0 The light intensity decline after the visible light of the (E) is transmitted through the Mars atmosphere is I=0.607I 0 The maximum value of the solar irradiation intensity of the Mars surface is 435.219W/m2, the minimum value is 299.251W/m2, and the average value is about 357.523W/m 2 。
In addition, mars have a small amount of dry ice clouds which are composed of large particles larger than 1 micrometer and are very dense to block sunlight from entering, the cloud layer pictures of OMEGA show that cloud layers can form shadows on the ground, different light depths tau exist along with the change of the thickness of the cloud layers, the value range of tau is estimated according to 0.2-1, and in the worst case (zenith angle of 60 degrees, atmospheric light depth tau=1), and the solar light intensity is 84.6123W/m only 2 . The intensity of the sun on the surface of the Mars is relatively complex.
In summary, APS sun sensor is adapted to 1390W/m on earth orbit or moon surface 2 ～1414W/m 2 The integral time is designed to be fixed at a certain integral time, and the change range of the solar light intensity of the solar sensor when the solar sensor works on the surface of the Mars is larger, namely 84.6123W/m 2 To 435.219W/m 2 The sun sensor has difficulty adapting to complex light intensity with the same integration time when the Mars surface is applied, and the sun sensor has not been experienced by Mars surface application.
Disclosure of Invention
The invention solves the technical problems that: the light intensity self-adaption method for the Mars APS sun sensor is provided for overcoming the defects of the prior art.
The solution of the invention is as follows:
an adaptive method for light intensity of an APS sun sensor of a Mars vehicle, comprising the following steps:
the first step: adjusting the integration time of 1024 steps into 64 control steps by using a control word mode, and carrying out discrete arrangement on the 64 control steps, wherein the 64 control steps comprise 64 control words, the integration time is X T of each control word, and T is the readout time of one row of pixels of the image sensor;
and a second step of: setting an upper limit of integration time;
and a third step of: setting a gray statistics high threshold gray_ hig _thr and a gray statistics low threshold gray_low_thr;
fourth step: setting a high pixel number threshold cap_gray_ hig _cnt_thr and a low pixel number threshold cap_gray_low_cnt_thr of gray analysis in a sun capture mode; setting a pixel number high threshold value track_gray_ hig _cnt_thr and a pixel number low threshold value track_gray_low_cnt_thr of gray analysis in a sun tracking mode;
fifth step: carrying out gray analysis on the acquired image to obtain the number ImgCntHig_Num larger than the gray statistics high threshold value gray_ hig _thr and the number ImgCntLow_Num larger than the gray statistics low threshold value gray_low_thr;
sixth step: in the acquisition mode, the following operations are performed:
6.1 judging whether the current integration time is larger than the upper limit of the integration time, if so, setting the integration time according to the upper limit of the integration time, otherwise, judging whether the number ImgCntHig_num larger than the gray statistics high threshold gray_ hig _thr is larger than cap_gray_ hig _cnt_thr, if so, entering the step 6.2, otherwise, entering the step 6.3;
6.2, judging whether the current integration time is greater than 0, if not, setting the integration time to 0, and exiting the capturing mode; if the integration time is greater than 0, judging whether the integration time exists between the upper limit of the current integration time and the lower limit of the integration time according to the 64 control files, if so, reducing the integration time according to a dichotomy, and if not, initializing a search state;
6.3 judging whether the number ImgCntLow_Num greater than the gray statistics low threshold value gray_low_thr is lower than cap_gray_low_cnt_thr, and if not, exiting the capturing mode; if the current value is lower than the preset value, the step 6.4 is entered;
6.4, judging whether the current integration time is smaller than the upper limit of the integration time, if not, setting the integration time according to the upper limit of the integration time; if yes, judging whether the integration time exists between the upper limit of the current integration time and the lower limit of the integration time according to the 64 control files, if yes, increasing the integration time according to a dichotomy, and if not, initializing a search state;
seventh step: in the tracking mode, the following operations are performed:
7.1 judging whether the current integration time is larger than the upper limit of the integration time, if so, setting the integration time according to the upper limit of the integration time, otherwise, judging whether the number ImgCntHig_num larger than the gray statistics high threshold value gray_ hig _thr is larger than the track_gray_ hig _cnt_thr, if so, entering the step 7.2, and if not, entering the step 7.3;
7.2 judging whether the current integration time is greater than 0, if not, maintaining the integration time to be 0, setting an angle calculation mark and starting angle calculation; if yes, the integral time is reduced according to the step pitch, and the angle is cleared to calculate a mark;
7.3 judging whether the ImgCntLow_Num is lower than the track_gray_low_cnt_thr, if not, considering that the current integration time is proper, setting an angle calculation mark and starting to perform angle calculation; if yes, 7.4 is entered;
7.4, judging whether the current integration time is smaller than the upper limit of the integration time, if not, setting the integration time according to the upper limit of the integration time, exiting the sun tracking, and transferring to the sun capturing; if yes, the mark is calculated according to the step-up integration time added by one, and the angle is cleared.
The image sensor adopted by the Mars APS sun sensor adopts an exposure mode of a rolling shutter door, the image sensor array is 1024 x 1024, and the adjustment range of the integration time is 1 xT-1024 xT.
In the first step, the control words corresponding to the 64 control files are distributed as follows: [1,2,4,6,8,10,12,14,16,18,20,24,28,32,36,40,46,52,58,66,74,82,90,100,110,120,130,140,150,160,170,190,210,230,250,270,290,310,330,350,370,390,410,430,450,470,490,510,530,550,570,600,630,660,690,730,770,810,850,890,930,970,1010,1022].
In the second step, the upper limit of the integration time is 31 xT, and the corresponding light intensity is about 20W/m 2 。
The adapted solar light intensity at integration time of 0 is 1000W/m 2 。
In the third step, the gray statistical high threshold is an image saturation value of 0.8 times.
In the third step, the gray statistic low threshold is 0.6 times of the image saturation value.
The image saturation value is 255.
Compared with the prior art, the invention has the beneficial effects that:
(1) The invention firstly establishes an automatic adjustment integration time table for the discrete distribution of the integration time of the image sensor, small integration time, small step distance, large integration time and large step distance. A control word for setting the upper limit of the integration time automatic adjustment, and the integration time adjustment range can be modified by an instruction.
(2) The invention can quickly adjust the integration time in the capturing mode, quickly approach the binary method, has wide criterion of the proper condition of the integration time, finely adjust the integration time in the tracking mode, adjust the integration time according to the step distance of 1, and finely judge the proper condition of the integration time, so that the highest gray level distribution of the solar bright spots is near 80% of the saturation point, and is suitable for the application of the surfaces of mars.
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FIG. 1 is a flowchart of automatic integration time adjustment in capture mode;
FIG. 2 is a flowchart of the automatic adjustment of integration time in tracking mode.
Detailed Description
The invention is further elucidated below in connection with the accompanying drawings.
The current automatic exposure or automatic light intensity adaptation is commonly seen in cameras, the gray level distribution analysis is carried out by using a histogram result, then an adjustment strategy of the integration time is determined, a large-capacity data memory is needed for carrying out histogram statistics by an APS sun sensor, the data update rate is seriously influenced, the APS sun sensor is simple in sun bright spots on an image formed by the sun, the background is simple, and therefore, a proper automatic adjustment method of the integration time is needed to be selected according to the imaging characteristics of the APS sun sensor.
The method comprises the steps of firstly, discretely distributing the integration time of an image sensor, small integration time and large step distance, and establishing an automatic adjustment integration time table. A control word for setting the upper limit of the integration time automatic adjustment, and the integration time adjustment range can be modified by an instruction.
The Mars APS sun sensor is an imaging sun sensor, and different light intensities are adapted through different integration times. The image sensor adopts the exposure mode of the rolling shutter door, and the integration time is adjusted according to the row reading time T as equivalent. Since the image sensor is 1024 rows, the integration time is adjusted in the range of 1×t to 1024×t.
The first step: the integration time of 1024 steps is adjusted into 64 control steps by using a control word mode, discrete arrangement is carried out, fine adjustment can be ensured during small integration time, quick adjustment can be realized during large integration time, the integration control steps are adjusted during the adjustment of the integration time, and the time distribution corresponding to the 64 control steps is as follows: [1,2,4,6,8,10,12,14,16,18,20,24,28,32,36,40,46,52,58,66,74,82,90,100,110,120,130,140,150,160,170,190,210,230,250,270,290,310,330,350,370,390,410,430,450,470,490,510,530,550,570,600,630,660,690,730,770,810,850,890,930,970,1010,1022]. The integration time is per control word x T.
And a second step of: setting the upper limit of the integration time, ensuring that the maximum value of the integration time is not exceeded when the integration time is automatically adjusted, and the default upper limit of the integration time is 31, wherein the integration time corresponds to the light intensity of about 20W/m 2 The adaptable solar light intensity is 1000W/m when the shortest time of the product is 0 2 。
And a third step of: the gray statistics high threshold gray_ hig _thr and the low threshold gray_low_thr are set, the default high threshold is 200, the low threshold is 150, the image saturation value is 255, the gray statistics high threshold is set according to the saturation value of 0.8 times of the high threshold, and the gray statistics low threshold is set according to the saturation value of 0.6 times of the low threshold.
Fourth step: a sun-capturing mode and a sun-tracking mode are set, a high threshold value cap_gray_ hig _cnt_thr, a default value 50, and a low threshold value cap_gray_low_cnt_thr of the number of pixels for gray analysis are set in the capturing mode, a default value 4, a high threshold value track_gray_ hig _cnt_thr, a default value 10, and a low threshold value track_gray_low_cnt_thr of the number of pixels for gray analysis are set in the tracking mode, and a default value 4.
Fifth step: the gray analysis is performed on the acquired image to obtain the number imgcnthig_num greater than the high threshold gray_ hig _thr and the number imgcntlow_num greater than the low threshold gray_low_thr.
Sixth step: in the capturing mode, firstly judging whether the current integration time is larger than the upper limit of the integration time, if so, setting the integration time according to the upper limit of the integration time, otherwise judging whether ImgCntHig_Num is larger than cap_gray_ hig _cnt_thr, if so, reducing the integration time according to a bisection method, firstly judging whether the minimum value of the integration time is 0, if so, setting the integration time to 0, then exiting capturing, if so, analyzing whether the integration time is larger than 0, if so, reducing the integration time according to the bisection method, and otherwise, initializing the searching state. If imgcnthig_num is not greater than cap_grad_ hig _cnt_thr, judging whether imgcntlow_num is lower than cap_grad_low_cnt_thr, if so, raising the integration time according to the dichotomy, firstly judging whether the integration time reaches the upper limit of the integration time, if so, setting the integration time as the upper limit of the integration time, if not, analyzing further, if not, analyzing intermediate values, if there is an intermediate value, lowering the integration time according to the dichotomy, if not, initializing the search state, if imgcntlow_num is higher than cap_grad_low_cnt_thr, if the integration time is proper in the capturing mode, and exiting capturing. As shown in fig. 1.
Seventh step: in the tracking mode, firstly judging whether the current integration time is larger than the upper limit of the integration time, if so, setting the integration time according to the upper limit of the integration time, otherwise judging whether ImgCntHig_Num is larger than track_gray_ hig _cnt_thr, if so, firstly judging whether the minimum value of the integration time is 0, if so, setting a 0 juxtaposition angle calculation mark for the integration time, if not, subtracting one step from the integration time, and clearing the angle calculation mark. If the imgcnthig_num is not more than the track_gray_ hig _cnt_thr, judging whether the imgcntlow_num is lower than the track_gray_low_cnt_thr, if so, firstly judging whether the integration time reaches an upper limit value, if so, exiting tracking and transferring to solar capture, if the integration time upper limit value is not reached, increasing the integration time according to the step distance by one, if the integration time is higher than the track_gray_low_cnt_thr, considering the integration time to be suitable in the tracking mode, obtaining the final suitable integration time of the solar sensor, then starting solar tracking, and starting solar attitude angle calculation. As shown in fig. 2.
The invention is used for coping with complex light intensity environments of Mars surfaces, creatively proposes an automatic adjustment control method based on the integration time of high and low gray thresholds by referring to an automatic exposure control method based on a brightness histogram and combining the solar bright spot characteristics of an APS sun sensor.
In order to realize the rapid high-precision output of the sun sensor on the sun capturing and the sun gesture, the product is provided with two working modes of capturing and tracking, the integral time is coarsely adjusted in the capturing mode, the gesture is only captured on the sun, but not output, the integral time is finely adjusted after the tracking is carried out, and the gesture calculation is carried out after the proper integral time is obtained.
The integration time is quickly adjusted in the capturing mode, the dichotomy approaches quickly, the criterion of proper integration time is large, the integration time is finely adjusted in the tracking mode, the integration time is properly judged to be finer according to the step distance of 1, and the highest gray distribution of the solar bright spots is located near 80% of the saturation point.
The light intensity adaptation range of the sun sensor can meet 20W/m 2 To 1000W/m 2 Can meet the application requirements of Mars surfaces.
What is not described in detail in the present specification is a known technology to those skilled in the art.

Claims (8)

1. The light intensity self-adaption method of the Mars APS sun sensor is characterized by comprising the following steps of:
the first step: adjusting the integration time of 1024 steps into 64 control steps by using a control word mode, and carrying out discrete arrangement on the 64 control steps, wherein the 64 control steps comprise 64 control words, the integration time is X T of each control word, and T is the readout time of one row of pixels of the image sensor;
and a second step of: setting an upper limit of integration time;
and a third step of: setting a gray statistics high threshold gray_ hig _thr and a gray statistics low threshold gray_low_thr;
fourth step: setting a high pixel number threshold cap_gray_ hig _cnt_thr and a low pixel number threshold cap_gray_low_cnt_thr of gray analysis in a sun capture mode; setting a pixel number high threshold value track_gray_ hig _cnt_thr and a pixel number low threshold value track_gray_low_cnt_thr of gray analysis in a sun tracking mode;
fifth step: carrying out gray analysis on the acquired image to obtain the number ImgCntHig_Num larger than the gray statistics high threshold value gray_ hig _thr and the number ImgCntLow_Num larger than the gray statistics low threshold value gray_low_thr;
sixth step: in the acquisition mode, the following operations are performed:
6.1 judging whether the current integration time is larger than the upper limit of the integration time, if so, setting the integration time according to the upper limit of the integration time, otherwise, judging whether the number ImgCntHig_num larger than the gray statistics high threshold gray_ hig _thr is larger than cap_gray_ hig _cnt_thr, if so, entering the step 6.2, otherwise, entering the step 6.3;
6.2, judging whether the current integration time is greater than 0, if not, setting the integration time to 0, and exiting the capturing mode; if the integration time is greater than 0, judging whether the integration time exists between the upper limit of the current integration time and the lower limit of the integration time according to the 64 control files, if so, reducing the integration time according to a dichotomy, and if not, initializing a search state;
6.3 judging whether the number ImgCntLow_Num greater than the gray statistics low threshold value gray_low_thr is lower than cap_gray_low_cnt_thr, and if not, exiting the capturing mode; if the current value is lower than the preset value, the step 6.4 is entered;
6.4, judging whether the current integration time is smaller than the upper limit of the integration time, if not, setting the integration time according to the upper limit of the integration time; if yes, judging whether the integration time exists between the upper limit of the current integration time and the lower limit of the integration time according to the 64 control files, if yes, increasing the integration time according to a dichotomy, and if not, initializing a search state;
seventh step: in the tracking mode, the following operations are performed:
7.1 judging whether the current integration time is larger than the upper limit of the integration time, if so, setting the integration time according to the upper limit of the integration time, otherwise, judging whether the number ImgCntHig_num larger than the gray statistics high threshold value gray_ hig _thr is larger than the track_gray_ hig _cnt_thr, if so, entering the step 7.2, and if not, entering the step 7.3;
7.2 judging whether the current integration time is greater than 0, if not, maintaining the integration time to be 0, setting an angle calculation mark and starting angle calculation; if yes, the integral time is reduced according to the step pitch, and the angle is cleared to calculate a mark;
7.3 judging whether the ImgCntLow_Num is lower than the track_gray_low_cnt_thr, if not, considering that the current integration time is proper, setting an angle calculation mark and starting to perform angle calculation; if yes, 7.4 is entered;
7.4, judging whether the current integration time is smaller than the upper limit of the integration time, if not, setting the integration time according to the upper limit of the integration time, exiting the sun tracking, and transferring to the sun capturing; if yes, the mark is calculated according to the step-up integration time added by one, and the angle is cleared.
2. The light intensity self-adaptation method of the Mars car APS sun sensor according to claim 1, wherein an image sensor adopted by the Mars car APS sun sensor adopts a rolling shutter exposure mode, an image sensor array is 1024 x 1024, and the adjustment range of integration time is 1 xT-1024 xT.
3. The light intensity self-adaptation method of the Mars car APS sun sensor according to claim 1, wherein in the first step, the control words corresponding to the 64 control steps are distributed as follows: [1,2,4,6,8,10,12,14,16,18,20,24,28,32,36,40,46,52,58,66,74,82,90,100,110,120,130,140,150,160,170,190,210,230,250,270,290,310,330,350,370,390,410,430,450,470,490,510,530,550,570,600,630,660,690,730,770,810,850,890,930,970,1010,1022].
4. The method according to claim 1, wherein in the second step, the integration time is up to 31×t, and the corresponding light intensity is about 20W/m 2 。
5. The light intensity adaptation method for an APS sun sensor of a Mars vehicle according to claim 1, wherein the adapted solar light intensity is 1000W/m when the integration time is 0 2 。
6. The method for adaptive intensity of APS sun sensor for Mars according to claim 1, wherein in said third step, the gray level statistical high threshold is 0.8 times the saturation value of the image.
7. The method according to claim 1, wherein in the third step, the gray level statistic low threshold is 0.6 times the image saturation value.
8. A method for adapting the intensity of an APS sun sensor for a Mars vehicle according to claim 6 or 7, wherein the saturation value of the image is 255.
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Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101231170A (en) * 2008-01-31 2008-07-30 北京控制工程研究所 Method for processing information of APS sun sensor

Family Cites Families (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6861633B2 (en) * 2002-06-20 2005-03-01 The Aerospace Corporation Microelectromechanical system optical sensor providing bit image data of a viewed image
CN100405017C (en) * 2007-06-22 2008-07-23 北京航空航天大学 Method and device for processing signal of hole array sun sensor
CN100414253C (en) * 2007-07-06 2008-08-27 北京航空航天大学 Digital sun sensor calibration method and device

Patent Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101231170A (en) * 2008-01-31 2008-07-30 北京控制工程研究所 Method for processing information of APS sun sensor

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
A review on sun position sensors used in solar applications;Lizbeth Salgado-Conrado et al.;Renewable and Sustainable Energy Reviews;全文 *
一种用于对日观测载荷的高精度高更新率太阳敏感器;常晔 等;空间控制技术与应用;第45卷(第6期);全文 *
基于SiP技术的单片集成数字式太阳敏感器;吴迪;陈纾;陈龙江;叶志龙;郑循江;;深空探测学报(01);全文 *

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